scholarly journals Sex differences in zonulin in affective disorders and associations with current mood symptoms

2021 ◽  
Author(s):  
Maget A ◽  
Dalkner N ◽  
Hamm C ◽  
Bengesser SA ◽  
Fellendorf F ◽  
...  
Keyword(s):  
Sex Differences ◽  
Affective Disorders ◽  
Mood Symptoms ◽  
Current Mood

Sex differences in the age of onset of affective disorders

1993 ◽  
Vol 34 (3) ◽  
pp. 187-191 ◽  
Author(s):  
Richard C. Evenson ◽  
Scott T. Meier ◽  
Brian J. Hagan
Keyword(s):  
Sex Differences ◽  
Affective Disorders ◽  
Age Of Onset

scholarly journals Sex differences in mortality among patients admitted with affective disorders in North Norway: a 33-year prospective register study

2016 ◽  
Vol 18 (3) ◽  
pp. 272-281 ◽  
Author(s):  
Anne Høye ◽  
Ragnar Nesvåg ◽  
Ted Reichborn-Kjennerud ◽  
Bjarne K. Jacobsen
Keyword(s):  
Sex Differences ◽  
Affective Disorders ◽  
Register Study ◽  
North Norway

Coping style and ecstasy use motives as predictors of current mood symptoms in ecstasy users

2013 ◽  
Vol 38 (10) ◽  
pp. 2465-2472 ◽  
Author(s):  
Rebecca M. Scott ◽  
Leanne Hides ◽  
J. Sabura Allen ◽  
Dan I. Lubman
Keyword(s):  
Coping Style ◽  
Mood Symptoms ◽  
Current Mood

Differences in Kynurenine Metabolism During Depressive, Manic, and Euthymic Phases of Bipolar Affective Disorder

2020 ◽  
Vol 20 (15) ◽  
pp. 1344-1352 ◽  
Author(s):  
Alexander Maget ◽  
Martina Platzer ◽  
Susanne A. Bengesser ◽  
Frederike T. Fellendorf ◽  
Armin Birner ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Kynurenic Acid ◽  
Rating Scale ◽  
Depression Scale ◽  
Hamilton Depression Scale ◽  
Monooxygenase Activity ◽  
Kynurenine Aminotransferase ◽  
Mood Symptoms ◽  
Kynurenine Metabolism ◽  
Current Mood

Background & Objectives: The kynurenine pathway is involved in inflammatory diseases. Alterations of this pathway were shown in psychiatric entities as well. The aim of this study was to determine whether specific changes in kynurenine metabolism are associated with current mood symptoms in bipolar disorder. Methods: Sum scores of the Hamilton Depression Scale, Beck Depression Inventory, and Young Mania Rating Scale were collected from 156 bipolar individuals to build groups of depressive, manic and euthymic subjects according to predefined cut-off scores. Severity of current mood symptoms was correlated with activities of the enzymes kynurenine 3-monooxygenase (ratio of 3-hydroxykynurenine/ kynurenine), kynurenine aminotransferase (ratio of kynurenic acid/ kynurenine) and kynureninase (ratio of 3-hydroxyanthranilic acid/ 3-hydroxykynurenine), proxied by ratios of serum concentrations. Results: Individuals with manic symptoms showed a shift towards higher kynurenine 3-monooxygenase activity (χ2 = 7.14, Df = 2, p = .028), compared to euthymic as well as depressed individuals. There were no differences between groups regarding activity of kynurenine aminotransferase and kynureninase. Within the group of depressed patients, Hamilton Depression Scale and kynurenine aminotransferase showed a significant negative correlation (r = -0.41, p = .036), displaying lower metabolism in the direction of kynurenic acid. Conclusion: Depression severity in bipolar disorder seems to be associated with a decreased synthesis of putative neuroprotective kynurenic acid. Furthermore, higher kynurenine 3-monooxygenase activity in currently manic individuals indicates an increased inflammatory state within bipolar disorder with more severe inflammation during manic episodes. The underlying pathophysiological mechanisms of the different affective episodes could represent parallel mechanisms rather than opposed processes.

scholarly journals Sex differences and the neurobiology of affective disorders

2018 ◽  
Vol 44 (1) ◽  
pp. 111-128 ◽  
Author(s):  
David R. Rubinow ◽  
Peter J. Schmidt
Keyword(s):  
Sex Differences ◽  
Affective Disorders

scholarly journals In search of sex-related mediators of affective illness

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Christopher Sikes-Keilp ◽  
David R. Rubinow
Keyword(s):  
Human Physiology ◽  
Sex Differences ◽  
Affective Disorders ◽  
Network Connectivity ◽  
Neural Function ◽  
Affective States ◽  
Related Factors ◽  
Affective Illness ◽  
Underlying Pathogenesis

AbstractSex differences in the rates of affective disorders have been recognized for decades. Studies of physiologic sex-related differences in animals and humans, however, have generally yielded little in terms of explaining these differences. Furthermore, the significance of these findings is difficult to interpret given the dynamic, integrative, and highly context-dependent nature of human physiology. In this article, we provide an overview of the current literature on sex differences as they relate to mood disorders, organizing existing findings into five levels at which sex differences conceivably influence physiology relevant to affective states. These levels include the following: brain structure, network connectivity, signal transduction, transcription/translation, and epigenesis. We then evaluate the importance and limitations of this body of work, as well as offer perspectives on the future of research into sex differences. In creating this overview, we attempt to bring perspective to a body of research that is complex, poorly synthesized, and far from complete, as well as provide a theoretical framework for thinking about the role that sex differences ultimately play in affective regulation. Despite the overall gaps regarding both the underlying pathogenesis of affective illness and the role of sex-related factors in the development of affective disorders, it is evident that sex should be considered as an important contributor to alterations in neural function giving rise to susceptibility to and expression of depression.

scholarly journals Correlations between objective behavioral features collected from mobile and wearable devices, and depressive mood symptoms in affective disorders: A systematic review (Preprint)

2017 ◽  
Author(s):  
Darius Adam Rohani ◽  
Maria Faurholt-Jepsen ◽  
Lars Vedel Kessing ◽  
Jakob Eyvind Bardram
Keyword(s):  
Systematic Review ◽  
Affective Disorders ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Objective Measure ◽  
Depressive Mood ◽  
Sensor Data ◽  
Replication Studies ◽  
Mood Symptoms ◽  
Behavioral Features

BACKGROUND Several studies have recently reported on the correlation between objective behavioral features collected via mobile and wearable technologies and depressive mood symptoms in affective disorders (unipolar disorder and bipolar disorder). However, individual studies have reported on different and sometimes contradicting results, and no quantitative systematic review of the correlation between objective behavioral features and depressive mood symptoms has been published. OBJECTIVE The objectives of this systematic review were to 1) provide an overview of correlations between objective behavioral features and depressive mood symptoms reported in the literature, and 2) investigate the strength and statistical significance of these correlations across studies. The answers to these questions could potentially help in the identification on which objective features have shown most promising results across studies. METHODS A systematic review of the scientific literature reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines was conducted. IEEE Xplore, ACM Digital Library, Web of Sciences, PsychINFO, Pubmed, DBLP computer science bibliography, HTA, DARE, Scopus and Science Direct were searched and supplemented by hand examination of reference lists. The search ended 04/27-2017 and was limited to studies published 2007-2017. RESULTS A total of 46 studies were eligible for the review. These studies identified and investigated 85 unique objective behavioral features covering 17 various sensor data inputs. These features can be categorized into seven overall categories. Several features were found to have statistically significant and consistent correlation directionality with mood assessment (e.g., the amount of home stay, sleep duration, vigorous activity), while others showed directionality discrepancies across the studies (e.g., amount of SMS sent, time you spend between locations, frequency of smartphone screen activity). CONCLUSIONS Several studies showed consistent and statistically significant correlations between objective behavioral features collected by mobile and wearable technology and depressive mood symptoms. Hence, continuous and every-day monitoring of behavioral aspects in affective disorders could be a promising supplementary objective measure to estimate depressive mood symptoms. However, the evidence is limited by methodological issues in individual studies and by a lack of standardization of 1) the collected objective features, 2) the mood assessment methodology, and 3) the statistical methods applied. Therefore, consistency in data collection and analysis in future studies is needed making replication studies as well as meta-analyses possible.

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